Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process

Peter Alexander Stentoft; Thomas Munk-Nielsen; Peter Steen Mikkelsen; Henrik Madsen; Luca Vezzaro; Jan Kloppenborg Møller

Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process

Peter Alexander Stentoft
, Thomas Munk-Nielsen
, Peter Steen Mikkelsen
, Henrik Madsen
, Luca Vezzaro
, Jan Kloppenborg Møller

Krüger Veolia Water Technologies

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Wastewater treatment aeration accounts for a large amount of societal electricity consumption. This abstract suggests MPC driven by stochastic differential equations and genetic optimization, under legal and equipment constraints to prioritize aeration in selected periods. Thereby we reduce costs and empower smart use of green electricity from e.g. wind turbines.

Original language	English
Title of host publication	Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control
Number of pages	2
Publisher	International Federation of Automatic Control
Publication date	2018
Article number	MoAPo1.30
Publication status	Published - 2018
Event	6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018) - Madison, United States Duration: 19 Aug 2018 → 22 Aug 2018

Conference

Conference	6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018)
Country/Territory	United States
City	Madison
Period	19/08/2018 → 22/08/2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Stochastic Systems
Genetic Algorithms
Process Control
Predictive Control
Water Pollution
Smart Power Applications

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Stentoft et al NMPC finalAccepted author manuscript, 183 KB

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@inproceedings{2fd98bea89f24ac5b50fdb1e43859e76,

title = "Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process",

abstract = "Wastewater treatment aeration accounts for a large amount of societal electricity consumption. This abstract suggests MPC driven by stochastic differential equations and genetic optimization, under legal and equipment constraints to prioritize aeration in selected periods. Thereby we reduce costs and empower smart use of green electricity from e.g. wind turbines.",

keywords = "Stochastic Systems, Genetic Algorithms, Process Control, Predictive Control, Water Pollution, Smart Power Applications",

author = "Stentoft, \{Peter Alexander\} and Thomas Munk-Nielsen and Mikkelsen, \{Peter Steen\} and Henrik Madsen and Luca Vezzaro and M{\o}ller, \{Jan Kloppenborg\}",

year = "2018",

language = "English",

booktitle = "Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control",

publisher = "International Federation of Automatic Control",

note = "6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018) ; Conference date: 19-08-2018 Through 22-08-2018",

}

Stentoft, PA, Munk-Nielsen, T, Mikkelsen, PS , Madsen, H , Vezzaro, L & Møller, JK 2018, Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process. in Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control., MoAPo1.30, International Federation of Automatic Control, 6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018), Madison, United States, 19/08/2018.

Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process. / Stentoft, Peter Alexander; Munk-Nielsen, Thomas; Mikkelsen, Peter Steen et al.
Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control. International Federation of Automatic Control, 2018. MoAPo1.30.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process

AU - Stentoft, Peter Alexander

AU - Munk-Nielsen, Thomas

AU - Mikkelsen, Peter Steen

AU - Madsen, Henrik

AU - Vezzaro, Luca

AU - Møller, Jan Kloppenborg

PY - 2018

Y1 - 2018

N2 - Wastewater treatment aeration accounts for a large amount of societal electricity consumption. This abstract suggests MPC driven by stochastic differential equations and genetic optimization, under legal and equipment constraints to prioritize aeration in selected periods. Thereby we reduce costs and empower smart use of green electricity from e.g. wind turbines.

AB - Wastewater treatment aeration accounts for a large amount of societal electricity consumption. This abstract suggests MPC driven by stochastic differential equations and genetic optimization, under legal and equipment constraints to prioritize aeration in selected periods. Thereby we reduce costs and empower smart use of green electricity from e.g. wind turbines.

KW - Stochastic Systems

KW - Genetic Algorithms

KW - Process Control

KW - Predictive Control

KW - Water Pollution

KW - Smart Power Applications

M3 - Article in proceedings

BT - Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control

PB - International Federation of Automatic Control

T2 - 6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018)

Y2 - 19 August 2018 through 22 August 2018

ER -

Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process

Abstract

Conference

UN SDGs

Keywords

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